资源论文Composite Multiclass Losses

Composite Multiclass Losses

2020-01-08 | |  56 |   38 |   0

Abstract

We consider loss functions for multiclass prediction problems. We show when a multiclass loss can be expressed as a “proper composite loss”, which is the composition of a proper loss and a link function. We extend existing results for binary losses to multiclass losses. We determine the stationarity condition, Bregman representation, order-sensitivity, existence and uniqueness of the composite representation for multiclass losses. We subsume existing results on “classification calibration” by relating it to properness and show that the simple integral representation for binary proper losses can not be extended to multiclass losses.

上一篇:Expressive Power and Approximation Errors of Restricted Boltzmann Machines

下一篇:High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity

用户评价
全部评价

热门资源

  • Learning to Predi...

    Much of model-based reinforcement learning invo...

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • The Variational S...

    Unlike traditional images which do not offer in...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...

  • Rating-Boosted La...

    The performance of a recommendation system reli...